# Systematic physics constrained parameter estimation of stochastic differential equations

@article{Peavoy2013SystematicPC, title={Systematic physics constrained parameter estimation of stochastic differential equations}, author={Daniel Peavoy and Christian L. E. Franzke and Gareth O. Roberts}, journal={Comput. Stat. Data Anal.}, year={2013}, volume={83}, pages={182-199} }

## 17 Citations

### New Trends in Ensemble Forecast Strategy: Uncertainty Quantification for Coarse-Grid Computational Fluid Dynamics

- Environmental ScienceArchives of Computational Methods in Engineering
- 2020

A new energy-budget-based stochastic subgrid scheme and a new way of parameterizing models under location uncertainty, both of which are based on randomized-initial-condition methods, are introduced.

### New Trends in Ensemble Forecast Strategy: Uncertainty Quantification for Coarse-Grid Computational Fluid Dynamics

- Environmental ScienceArchives of Computational Methods in Engineering
- 2020

Numerical simulations of industrial and geophysical fluid flows cannot usually solve the exact Navier–Stokes equations. Accordingly, they encompass strong local errors. For some applications—like…

### Stochastic Climate Theory

- Computer Science
- 2016

This chapter provides a conceptual framework for stochastic modelling of deterministic dynamical systems based on the Mori-Zwanzig formalism and expresses standard model reduction methods such as averaging and homogenization which eliminate the memory term.

### Reduced-space Gaussian Process Regression for data-driven probabilistic forecast of chaotic dynamical systems

- Computer Science
- 2017

### Mixing and fluid dynamics under location uncertainty

- Environmental Science
- 2017

This thesis develops, analyzes and demonstrates several valuable applications of randomized fluid dynamics models referred to as under location uncertainty. The velocity is decomposed between…

### Comparison of stochastic parameterizations in the framework of a coupled ocean–atmosphere model

- Environmental Science, PhysicsNonlinear Processes in Geophysics
- 2018

Abstract. A new framework is proposed for the evaluation of stochastic subgrid-scale parameterizations in the context of the Modular Arbitrary-Order Ocean-Atmosphere Model (MAOOAM), a coupled…

### Stochastic climate theory and modeling

- Environmental Science
- 2014

Stochastic methods are a crucial area in contemporary climate research and are increasingly being used in comprehensive weather and climate prediction models as well as reduced order climate models and an overview of stochastic climate theory from an applied mathematics perspective is provided.

### UvA-DARE (Digital Academic Repository) Stochastic climate theory

- Computer Science
- 2016

This chapter provides a conceptual framework for stochastic modelling of deterministic dynamical systems based on the Mori-Zwanzig formalism and expresses standard model reduction methods such as averaging and homogenization which eliminate the memory term.

### Calculating State-Dependent Noise in a Linear Inverse Model Framework

- Mathematics
- 2017

AbstractThe most commonly used version of a linear inverse model (LIM) is forced by state-independent noise. Although having several desirable qualities, this formulation can only generate long-term…

### Inverse stochastic–dynamic models for high-resolution Greenland ice core records

- Environmental Science
- 2017

Abstract. Proxy records from Greenland ice cores have been studied for several decades, yet many open questions remain regarding the climate variability encoded therein. Here, we use a Bayesian…

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